At Synopsys, you will work on computational lithography models that enable the next generation of semiconductor manufacturing, and the team you join will expect you to bring both rigor and creativity to problems that have never been solved before.
What You'll Be Doing
Design and implement optimization techniques that reduce model calibration runtime without sacrificing accuracy, working directly with large-scale empirical datasets from leading-edge semiconductor processes
Prototype and develop new mathematical models for lithography simulation, translating specifications into production-quality C++ code integrated into the Proteus product line
Calibrate and tune complex non-linear model parameters using statistical analysis, numerical optimization, and domain-specific heuristics
Collaborate with cross-functional teams including product engineering, field support, and customer-facing teams to understand technical requirements and integrate modeling solutions into existing workflows
Analyze outlier data points and develop sampling strategies that improve model robustness and generalization across process variations
Maintain and extend existing computational lithography models, diagnosing performance bottlenecks and correctness issues in a large, mature codebase
Work directly with field engineers and customers to troubleshoot model behavior, gather requirements for new features, and validate solutions against real manufacturing data
The Impact You Will Have
Enable semiconductor manufacturers to bring next-generation nodes to production faster by delivering models that calibrate in hours instead of days
Unlock previously unsolvable lithography challenges by developing optimization techniques that handle higher complexity and tighter tolerances than existing methods
Improve model accuracy across a wider range of manufacturing conditions, reducing costly silicon respins and accelerating time to market for customers
Strengthen Synopsys' competitive position in computational lithography by contributing novel algorithms and methods that differentiate the Proteus platform
Reduce customer escalations and support load by building models that are more robust, interpretable, and easier to tune in the field
Influence product roadmap and strategy by identifying technical gaps and opportunities based on direct customer interaction and data analysis
Mentor and raise the technical bar for the broader modeling team by sharing deep expertise in optimization, numerical methods, and software engineering best practices
What You'll Need
PhD in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or related field strongly preferred (recent PhD graduates encouraged to apply; PhD with 1-2 years of industry experience ideal), OR MS in a related field with approximately 5 years of directly relevant industry experience in computational modeling, optimization, or numerical methods
Strong programming skills in C++ for performance-critical numerical software and Python for prototyping and data analysis
Deep background in physical modeling, statistical analysis, and optimization methods, with hands-on experience applying these techniques to real-world problems
Solid foundation in numerical computation, including experience with algorithms for solving non-linear systems, parameter fitting, and convergence analysis
Demonstrated ability to analyze complex datasets, identify patterns and outliers, and translate findings into actionable model improvements
Experience in computational lithography, optical modeling, or image processing is a strong plus
Background working on large, complex software projects with multiple contributors and long product lifecycles is a strong plus
Who You Are
You can take a vague customer complaint about model accuracy, dig into the data, isolate the root cause, and propose a fix that addresses the underlying issue without breaking existing workflows
You know when to optimize for speed and when to optimize for clarity, and you can defend that tradeoff to a senior engineer or a product manager without hand-waving
You are comfortable presenting technical results to a mixed audience, whether that is walking a field engineer through a calibration workflow or explaining a convergence failure to a PhD researcher
You do not get stuck when the data is messy or the requirements are incomplete, you make progress with what you have and course-correct as you learn more
You care about the craft of writing maintainable code, not just code that works today, and you leave the codebase better than you found it
You ask questions that cut to the core of a problem, and you listen carefully to the answers, especially when they come from people with different expertise than yours
The Team You'll Be Part Of
You will join the Proteus R&D team within the EDA Group, focused on computational lithography modeling for leading-edge semiconductor manufacturing. This is a collaborative, technically deep team working on problems at the intersection of physics, mathematics, and high-performance software engineering. The team works closely with cross-functional groups including product engineering, field support, and customers to deliver modeling solutions that enable next-generation chip manufacturing. You will have the opportunity to learn deeply within specific modeling topics while gaining broad exposure to new technologies across the computational lithography domain.
Rewards and Benefits
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.
